Instructions to use Yonadav/prophets_classifier_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Yonadav/prophets_classifier_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Yonadav/prophets_classifier_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Yonadav/prophets_classifier_model") model = AutoModelForSequenceClassification.from_pretrained("Yonadav/prophets_classifier_model") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
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by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:26565dd13747aa83cb60892e6ff7f9b42a4cb13d551a9ef08f07bc7dab92d853
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size 267832560
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